Processing of Cryptographic Function Identification Based on Multi-feature Progressive Model

Wei Lin, Yuefei Zhu, and Ruijie Cai

Abstract—Research on cryptographic function identification is of great significance in malicious code analysis, software vulnerability analysis and other fields. The current cryptographic function identification algorithm has the problem of low identification accuracy because of its single feature. In order to solve this problem, we proposed an improved method of cryptographic function identification based on multi-feature progressive approach to identify cryptographic functions by using data flow analysis in software. The experimental results show that, compared to current methods, it can identify the accurate cryptographic function accurately, and the accuracy is improved.